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      Comparing Kaiser Permanente Members to the General Population: Implications for Generalizability of Research

      research-article
      , PhD 1 , 2 , , MUS 1 , , PhD 1 , , PhD 1 , 2 , , PhD 1 , 2 ,
      The Permanente Journal
      The Permanente Press
      Evidence, Performance, Population-Based

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          Abstract

          Introduction

          Insight into the characteristics of populations from which research samples are drawn is essential to understanding the generalizability of research findings. This study characterizes the membership of Kaiser Permanente and compares members to the population of the communities in which they live.

          Methods

          This study is a descriptive comparison of population distributions for Kaiser Permanente members vs the general population within counties in which Kaiser Permanente operates. Kaiser Permanente data on demographics, membership, geographically linked census data, and chronic condition prevalence were compared with community data drawn from the US Census and the Behavioral Risk Factor Surveillance System.

          Results

          Overall, Kaiser Permanente members were older (50% aged 40 or older compared to 45.8% of the general population) and more likely to be female (51.8% vs 50.5% of the general population). Distribution by race and ethnicity was similar for all Regions combined but varied somewhat within Regions. Distribution by neighborhood-linked income, education, and social vulnerability was similar between Kaiser Permanente and the community. Prevalence of 6 of 7 chronic conditions was higher in the community than in Kaiser Permanente, with differences ranging from 0.5% for depression to 7.7% for hyperlipidemia.

          Conclusion

          The demographic characteristics of Kaiser Permanente members are similar to the general population within each of the Kaiser Permanente Regions. Overall, the size and diversity of the Kaiser Permanente membership offers an effective platform for research. This approach to comparing health system members with the larger community provides valuable context for interpreting real-world evidence, including understanding the generalizability of research and of measures of system performance.

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          Most cited references18

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          Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies.

          (2004)
          A WHO expert consultation addressed the debate about interpretation of recommended body-mass index (BMI) cut-off points for determining overweight and obesity in Asian populations, and considered whether population-specific cut-off points for BMI are necessary. They reviewed scientific evidence that suggests that Asian populations have different associations between BMI, percentage of body fat, and health risks than do European populations. The consultation concluded that the proportion of Asian people with a high risk of type 2 diabetes and cardiovascular disease is substantial at BMIs lower than the existing WHO cut-off point for overweight (> or =25 kg/m2). However, available data do not necessarily indicate a clear BMI cut-off point for all Asians for overweight or obesity. The cut-off point for observed risk varies from 22 kg/m2 to 25 kg/m2 in different Asian populations; for high risk it varies from 26 kg/m2 to 31 kg/m2. No attempt was made, therefore, to redefine cut-off points for each population separately. The consultation also agreed that the WHO BMI cut-off points should be retained as international classifications. The consultation identified further potential public health action points (23.0, 27.5, 32.5, and 37.5 kg/m2) along the continuum of BMI, and proposed methods by which countries could make decisions about the definitions of increased risk for their population.
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            Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration.

            Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalizability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies, and cross-sectional studies, and 4 are specific to each of the 3 study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors, and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, 1 or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site (www.strobe-statement.org) should be helpful resources to improve reporting of observational research.
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              Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.

              To illustrate the problem of generalizability of epidemiological findings derived from a single population using data from the Rochester Epidemiology Project and from the US Census. We compared the characteristics of the Olmsted County, Minnesota, population with the characteristics of populations residing in the state of Minnesota, the Upper Midwest, and the entire United States. Age, sex, and ethnic characteristics of Olmsted County were similar to those of the state of Minnesota and the Upper Midwest from 1970 to 2000. However, Olmsted County was less ethnically diverse than the entire US population (90.3% vs 75.1% white), more highly educated (91.1% vs 80.4% high school graduates), and wealthier ($51,316 vs $41,994 median household income; 2000 US Census data). Age- and sex-specific mortality rates were similar for Olmsted County, the state of Minnesota, and the entire United States. We provide an example of analyses and comparisons that may guide the generalization of epidemiological findings from a single population to other populations or to the entire United States. Copyright © 2012 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Perm J
                tpj
                tpj
                The Permanente Journal
                The Permanente Press
                1552-5767
                1552-5775
                2023
                12 May 2023
                : 27
                : 2
                : 87-98
                Affiliations
                [1] 1Kaiser Permanente Research and Quality Measurement , Pasadena, CA, USA
                [2] 2Kaiser Permanente Bernard J Tyson School of Medicine , Pasadena, CA, USA
                Author notes
                [*]Elizabeth A McGlynn, PhD Elizabeth.A.McGlynn@ 123456kp.org
                Author information
                http://orcid.org/0000-0003-3833-472X
                Article
                TPJ-22-172
                10.7812/TPP/22.172
                10266863
                37170584
                a68a3223-cebf-42b8-82c0-1a021ce3ef71
                © 2023 The Authors.

                Published by The Permanente Federation LLC under the terms of the CC BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                Page count
                Tables: 2, References: 28, Pages: 12
                Categories
                Original Research
                health-services-research, Health services research
                integrated-delivery-systems, Integrated delivery systems
                value-based-and-high-value-care, Value-based and high-value care

                evidence,performance,population-based
                evidence, performance, population-based

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